Lifetime Intimate Partner Violence (IPV) Against Mozambican Women: Individual and Contextual Level Factors Driving Its Prevalence
Bibliographic record
Abstract
Abstract Background Intimate partner violence (IPV) remains a significant public health issue in Mozambique. This study uses data from the 2022-2023 Mozambique Demographic and Health Survey (DHS) to examine the prevalence and sociodemographic determinants of Lifetime IPV among women. Methods A nationally representative sample of 4,813 women aged 15-49 was analyzed to assess the prevalence of Lifetime IPV. Logistic regression models were used to identify individual- and contextual-level factors associated with Lifetime IPV. Results Nearly 1 in 4 women (23.07%) reported experiencing physical abuse from a current or former partner in their lifetime. Marital status emerged as a key individual-level determinant, with married, cohabitating, and separated women being at significantly higher odds of experiencing IPV compared to women who had never been in a union. Educational attainment and current employment were also associated with increased odds of IPV. Similarly, women who justified physical abuse had higher odds of experiencing IPV. Additionally, husbands/partners’ alcohol consumption was one of the strongest predictors, nearly tripling the odds of Lifetime IPV. Finally, the effect modification between marital status and education showed that the intersection of these factors further shaped IPV risk. At the contextual level, provincial disparities were observed, with Cabo Delgado and Manica showing the highest IPV prevalence, while Inhambane and Gaza had the lowest. Conclusion This study provides updated data on the prevalence of Lifetime IPV in Mozambique and highlights key individual and contextual factors contributing to IPV. The findings underscore the need for targeted interventions addressing socio-cultural norms, improving educational opportunities, mitigating alcohol consumption, and implementing province-specific strategies to reduce IPV and enhance women’s safety across Mozambique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".